Visual inspection systems for the analysis of moving web materials have proven critical to modern manufacturing operations. Industries as varied as metal fabrication, paper, non-wovens, and films rely on these automated inspection systems for both product certification and online process monitoring.
An automated visual inspection system for products manufactured on a continuously moving web typically utilizes one or more image capture devices to capture images of the web during manufacturing. Analysis computers apply image processing algorithms to detect anomalies that represent potential defects within the web. Areas of the web containing anomalies may be discarded if the anomalies rise to a classification level of a defect for a given product, or may be processed into other products that would be unaffected by the anomaly.
Linescan or linear array cameras are example image capture devices commonly used in manufacturing of moving materials. These cameras have a single array of pixel sensors for capturing image data. For example, an automated visual inspection system may utilize multiple line-scan cameras arranged to span the entire width of the moving web. Each of the line-scan cameras may include a linear arrangement of photodiode sensors that provide a line segment of image data (e.g., 2048×1 pixels). The collective image data provided by the arrangement of multiple line-scan cameras represents a single line of image data spanning the entire web in the cross-web direction. Other example image capture devices include multi-line matrix cameras, contact image sensors (CISs), and a raster-scan camera in which a laser sweeps across a defined portion of the web to generate image data.
In many cases, conventional visual inspection systems suffer from intra-device detection non-uniformity with respect to the individual image capture devices. That is, intra-device non-uniformity within one or more of the image capture devices may cause substantially identical web anomalies to be classified differently as a result of the anomalies lying within different areas of the field of view of the image capture device. Potential causes of this intra-device non-uniformity can include variations in the optical arrangement (e.g., lens profile) of the device, non-uniform illumination, characteristics of the material itself (e.g., polarization), and variance in light interaction with the material (e.g., angle effects) across the field of view of the image capture device.